Effect of Vitamin D3 Supplementation in the First 2 Years of Life on Psychiatric Symptoms at Ages 6 to 8 Years

This secondary analysis of a randomized clinical trial investigates the effect of increased vitamin D supplementation up to age 2 years on the risk of internalizing, externalizing, and total psychiatric problems at ages 6 to 8 years.


Biochemical analyses
Maternal serum samples were collected as part of routine maternity clinic follow-up visits at 6-27 weeks of gestation (mean = 11.3, standard deviation (SD) = 1.9) and stored in the Finnish Maternity Cohort serum bank, organized by the National Institute for Health and Welfare. Childhood serum samples were collected at ages one and two years. The IDS-iSYS fully automated immunoassay system with chemiluminescence detection (Immunodiagnostic Systems Ltd., Bolton, UK) was used in the analysis of 25-hydroxyvitamin D. The method has been demonstrated to have a good linear agreement with liquid chromatography in tandem with mass spectroscopy (LC-MS, R 2 =0.942, in-house comparison of 67 samples). Mean (95% Confidence Interval (CI) value for the ratio of IDS-iSYS 25(OH)D to LC-MS 25(OH)D is 0.73 (0.68; 0.78) while intra-assay variations were 7%. Analysis took place at the Pediatric Research Centre, University of Helsinki. Our laboratory participates in the inter-laboratory quality assessment scheme for vitamin D, DEQAS (Charing Cross Hospital, London, UK).

Attrition analysis
In an attrition analysis, we found that children who did not take part in the current study (n = 628), either due to non-participation in VIDI2 or non-completion of the CBCL questionnaire, had parents with lower attained education, and mothers with lower mean 25(OH)D concentrations during pregnancy (32.3 ng/mL vs 33.6 ng/mL), who smoked more often (20% vs 14%) and had shorter length of breastfeeding (10.3 vs 11.2 months), compared to those who took part in the follow-up (eTable 1). Differences between non-participants and participants did not vary between supplementation groups and the attrition rate was similar. 13 children were not included in the attrition analysis, 12 of whom did not fulfil inclusion criteria and one who was diagnosed with a rare genetic disorder after study recruitment To account for potential attrition bias regarding internalizing and/or externalizing behavior between participants and non-participants, we compared the rank-normalized values, according to the Blom formula, 2 of subscales from Infant-Toddler Social and Emotional Assessment (ITSEA) questionnaire assessed in our previous study at 2 years of age. 3 There were no significant differences between children lost to follow-up and children participating in the current study (Mean difference (MD) 0.03 (95% CI -0.12 to 0.18, P = .69 for externalizing behavior) MD 0.02 (95% CI -0.14 to 0.17, P = .82) for internalizing behavior).

Sensitivity analysis
To assess the potential impact of missing data, we reran the Model 1 analysis excluding individuals lacking data on maternal depressive symptoms (n = 28). For internalizing problems, the regression coefficient in the linear model using this approach was -0,21 (95% CI; -0.43 to 0.01, p = .07) and the OR for clinically significant problems was 0.42 (95% CI 0.18 to 0.96, p = .04), i.e., of the same significance level, magnitude, and direction as in the full sample. A similar lack of difference between the larger and smaller sample size was seen for externalizing, and total problems. Likewise, when using means substitution for those missing CES-D data to retain the entire sample in the analysis, findings for Model 2 were similar as those currently reported. For example, the regression coefficient in the linear model using this approach was -0,16 (95% CI; -0.37 to 0.05, p = .14) and the OR for clinically significant problems was 0.44 (95% CI 0.19 to 0.98, p = .04). In other words, the smaller sample size in Model 2 did most likely not influence/bias the results in a meaningful manner.

Inverse probability weighting analyses testing the impact of attrition
Inverse probability weighting (IPW) was used to assess whether findings might have been impacted by attrition bias. The probability of taking part in the 6-8-year follow-up study was assessed as a function of baseline covariates associated with non-participation using logistic regression. We then estimated the association between vitamin D supplementation and clinically significant internalizing problems at age 6-8 years weighting the participants by the inverse of their probability of follow-up participation. Running IPW estimation, children in the 1200 IU supplementation group had a 0.07 (95% CI 0.00 to 0.14; P=.04) lower probability of having clinically significant internalizing problems compared to children in the 400 IU group, corresponding to an OR of 0.40 (95% CI 0.17 to 0.95; P=.04), i.e., of the same magnitude as in the main analysis, ruling out attrition bias.

Interaction
To explore the potential interplay between supplementation status and maternal pregnancy vitamin D status, the supplementation groups were further stratified by maternal 25(OH)D status. A 30 ng/mL cutoff point was chosen a priori, based upon previous literature. 4 An interaction term was calculated by multiplying supplemental group status with maternal 25(OH)D group status. This product term was then entered into a series of linear and logistic regression models as a predictor variable together with the supplementation group and 25(OH)D group variables. Outcome measurements were internalizing, externalizing, and total problem scores in the linear regression models, and the dichotomous clinically significant problems variables in the logistic regression models. In the linear regression models, P-values for the interaction term were 0.22, 0.30, and 0.09 for the three outcome variables, respectively. The corresponding P-values for the logistic regression models were 0.59, 0.12, and 0.24, respectively.
An analysis split by sex demonstrated a higher prevalence of total problems (9% vs 2 %), internalizing problems (11% vs 6%), and externalizing problems (15% vs 4%) in boys compared to girls (see eTables 3 and 4 for participant characteristics divided by sex). To account for potential statistical interaction, a sex * intervention group product term was created and entered as the second step in three separate logistic regression models, with dichotomous CBCL internalizing problems, dichotomous CBCL externalizing problems, and dichotomous CBCL total problems, respectively, as the outcome variables. No significant interaction was found for internalizing or externalizing problems (omnibus test of model coefficients was .26, and .52, respectively. For total problems, however, the interaction test was significant (P = .02) when comparing a model controlling for supplementation group, and sex, compared to a model also including the interaction term. Neither the analysis with sexes combined, nor the one split by sex, demonstrated a significant association between the supplementation group and the dichotomous total problems outcome variable, however. Given this, as well as the low total number of children with T values above the clinical cut-off point for total problems, all analyses were performed with sexes combined.  An additional 13 children were originally included in the study population, 12 of whom were excluded due to not fulfilling inclusion criteria and 1 who was diagnosed with a rare genetic disorder after inclusion. These children were not included in the attrition analysis. Psychiatric symptoms assessed using the Childhood Behavior Checklist. In linear models, raw scores were square root transformed due to skewness and converted to Z-scores (0 = mean, 1 = 1 SD). In logistic models, scores were converted to T scores and dichotomized at 64 or above to reflect clinically significant problems. ORs and 95% CIs from logistic regression analyses show odds of belonging to a group with clinically significant problems per unit increase of 25(OH)D concentration.